For the safe and economical construction of embankment dams, the mechanical behaviour of the rockfill materials used in the dam’s shell must be analyzed. The characterization of rockfill materials with specified shear strength is difficult and expensive due to the presence of particles greater than 500 mm in diameter. This work investigates the feasibility of using an extreme gradient boosting (XGBoost) computing paradigm to estimate the shear strength of rockfill materials. To train and validate the proposed XGBoost model, a total of 165 databases obtained from the literature are chosen. The XGBoost model was compared against support vector machine (SVM), adaptive boosting (AdaBoost), random forest (RF), and K‐nearest neighbor (KNN) models described in the literature. XGBoost beats SVM, RF, AdaBoost, and KNN models in terms of performance evaluation metrics such as coefficient of determination (R²), Nash–Sutcliffe coefficient (NSE), and error in the root mean square ratio (RMSE) to the standard deviation of the measured data (RSR). The results demonstrated that the XGBoost model has the highest prediction performance with (R² = 0.9707, NSE = 0.9701, and RSR = 0.1729), followed by the SVM model with (R² = 0.9655, NSE = 0.9639, and RSR = 0.1899), RF (R² = 0.9545, NSE = 0.9542, and RSR = 0.2140), the AdaBoost model with (R² = 0.9390, NSE = 0.9388, and RSR = 0.2474) and the KNN model with (R² = 0.6233, NSE = 0.6180, and RSR = 0.6181). A sensitivity analysis has been conducted to ascertain the impact of each investigated input parameter. This study demonstrates that the established XGBoost model for estimating the shear strength of rockfill materials is reliable.

In a combined piled raft foundation (CPRF) both raft and piles take their share of the total load applied. However, in practice, the contribution of a raft in taking load is usually ignored and the load is assumed to be supported on piles. This way of CPRF becomes excessively conservative and uneconomical. To economize the design, relative load sharing of raft and piles in CPRF has to be found. In this connection, different simplified methods have been developed, each one with some limitations. In this study, three simplified methods have been applied to two cases of pile‐raft systems. The methods include Randolph, Poulos‐Davis‐Randolph, and modified Poulos‐Davis‐Randolph. The first case is a hypothetical case consisting of a 12 m × 12 m raft supported on a square group of nine piles. The second case study is an actual eight‐story building to be constructed in Peshawar, Pakistan. The building is supported on a pile‐raft system, with raft resting on very soft clay underlain by dense sand. The two case studies are also modelled in the finite element program PLAXIS 3D for comparison. The results of all the simplified methods are comparable with PLAXIS 3D. However, the Randolph method is much closer to PLAXIS 3D for the two cases studied. Furthermore, it is also shown that piles in a piled raft system can be used as “stress reducers” as well as a “settlement reducers.” Additionally, the effect of interaction factors is also evaluated with the s/d ratio as well as with varying soil stiffness. It was concluded that ignoring these factors leads to a very unsafe design of the pile‐raft system.

The mechanical behavior of the rockfill materials (RFMs) used in a dam’s shell must be evaluated for the safe and cost-effective design of embankment dams. However, the characterization of RFMs with specific reference to shear strength is challenging and costly, as the materials may contain particles larger than 500 mm in diameter. This study explores the potential of various kernel function-based Gaussian process regression (GPR) models to predict the shear strength of RFMs. A total of 165 datasets compiled from the literature were selected to train and test the proposed models. Comparing the developed models based on the GPR method shows that the superlative model was the Pearson universal kernel (PUK) model with an R-squared (R²) of 0.9806, a correlation coefficient (r) of 0.9903, a mean absolute error (MAE) of 0.0646 MPa, a root mean square error (RMSE) of 0.0965 MPa, a relative absolute error (RAE) of 13.0776%, and a root relative squared error (RRSE) of 14.6311% in the training phase, while it performed equally well in the testing phase, with R² = 0.9455, r = 0.9724, MAE = 0.1048 MPa, RMSE = 0.1443 MPa, RAE = 21.8554%, and RRSE = 23.6865%. The prediction results of the GPR-PUK model are found to be more accurate and are in good agreement with the actual shear strength of RFMs, thus verifying the feasibility and effectiveness of the model.

In deep foundations, the pile group and the pile raft are generally used. To date, the contribution of the raft is not taken into account in the design, even when the raft is in contact with the soil and the whole system is therefore considered to work as a pile group foundation. In a combined pile raft system, the raft takes a considerable portion of the applied load, depending upon the number of piles, the spacing to diameter ratio of the piles, and the length to diameter ratio. In this paper, an experimental investigation is carried out to study the response of small-scale pile group and piled raft models with a varying number of piles subjected to both vertical and lateral loads. Additionally, the response mechanism of these models to both types of loads is also studied. A comparison was made between these models. It was found that, unlike the pile group, the piled raft provides considerably high stiffness to both types of loads, and the difference between the stiffness of both systems decreases as the number of piles increases. By comparing the response of the piled raft and the pile group with the same number of piles under the same vertical and lateral load, it was concluded that the piled raft response to the lateral and vertical loads was much stiffer than the pile group response. The lateral deflection and the vertical settlement of the piled raft were less than those of the pile group with the same pile configuration. This effective response of the piled raft to the vertical and lateral loads was due to the raft contribution in resisting the vertical and lateral loads. Moreover, with the increase in the number of piles, the vertical and lateral contribution of the raft decreases.